Enhancing Interpretability of AI-driven Tools for Health: A Science Communication Approach
This presentation engages with a communicative approach to delve into the interpretability of AI-driven tools for health. The objective is to illustrate a work in progress of using a proposed Box of Questions for Communicating AI4H to achieve end-users-oriented, intelligible explanations. Overall, the presentation will reflect on how embracing a communicative strategy when incorporating AI-driven tools in health and biomedical research can augment transparency as an attribute of the innovation and adoption processes. Ultimately, it underscores how diverse strategies for achieving comprehensible communication can form an integral part of the adoption processes for building trust in AI-driven technologies for health.
PhD Candidate, Communication and Media Program-University of Calgary
Ms. Salgado is experienced in science communication, community outreach, and crisis communications with local and international organizations.Read More
As a doctoral candidate at the University of Calgary, she has been working in the fields of Responsible AI, AI narratives and policymaking, and intersections between communication and AI’s ethical values, including public trust. She is a graduate of the London School of Economics AI Ethics course, the first cohort of the University of Montreal-MILA course on Responsible AI and Human Rights, and the Alberta Machine Learning Institute (Amii) Kickstart Program. She has worked as a research consultant for a project on gender equality and inclusion in AI with MILA – Quebec Artificial Intelligence Institute. A cross-pollinated approach based on learnings from Science Communication and Studies of Science and Technology Critical Studies informs Ms. Salgado’s interest in issues of Responsible AI, transparency, and interpretability from a user-centred design approach.Read Less